SULI available research projects

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Summer 2021

Elucidating the Role of Hydrogen Bond Donor and Acceptor on Solvation in Deep Eutectic Solvents

Deep eutectic solvents (DESs) are homogenous mixtures formed through the combination of a hydrogen bond donor (HBD) and hydrogen bond acceptor (HBA).  The physico-chemical properties of DESs (e.g., viscosity, hydrophobicity, melting point/glass transition temperature) can generally be modulated by tailoring the chemical structure and/or the relative molar ratio of HBA/HBD. To better predict the performance of DESs when they are used in chemical separations and catalysis, an understanding of their solvation interactions with dissolved molecules is essential. Until now, various empirical polarity scales based on solvatochromic probes have been used to characterize DESs.  However, the polarity values measured by solvatochromic probes usually fall within a narrow range and do not adequately explain experimental observations when examining DESs with different chemical make-up.  In this work, inverse chromatography will be used to characterize the solvation interactions of DESs containing a multitude of HBA and HBD combinations. Results from these studies will allow for various DES solvation interactions to be determined, including hydrogen bond acidity, hydrogen bond basicity, pi-pi and n-pi interactions, dispersion interactions, and dipolar/ion dipole interactions. The determined solvation characteristics will be used to develop a molecular model that describes the role DESs play in separations processes. This project will expose the SULI student to a wide range of different skills including:  synthesis, purification, and characterization of DESs; chromatographic characterization; and computational modeling.

Research area:  Analytical Chemistry
Mentor:  Jared Anderson

 

Synthesis and characterization of complex metal pnictides

Transition and rare-earth metal pnictides exhibit a diverse range of properties ranging from thermoelectric materials to high-temperature superconductors. Our research group work on synthesis, structural and properties characterization of novel complex pnictide materials containing transition and/or rare-earth metals. The project will include solid-state synthesis of novel compounds, determination of their crystal structure, and characterization of the electrical and heat transport properties.

Research area:  Materials Sciences
Mentor:  Kirill Kovnir

Catalytic Transformations of Biorenewables

The project is aimed to transform molecules derived from biorenewable sources into commodity chemicals. The student will learn to synthesize and characterize advanced catalysts to perform these transformations under mild conditions in an energy efficient manner. In addition to learn materials characterization techniques, the student will learn methods to monitor reaction progress and to identify target products. Methods may include X-ray diffraction, microscopy, surface physi- and chemisorption, UV/Vis, Infrared, fluorescence and/or NMR spectroscopy, and GC/MS.

Research area:  Renewable Energy Sciences and Technologies
Mentor:  Igor Slowing

Hybrid nanostructures for catalysis

Students will participate in a project aimed to prepare smart multifunctional nanodevices for catalyzing sequences of chemical reactions to convert biomass related products into biorenewable fuels and chemical commodities. The nanostructured materials will be composed of organic and inorganic species that will work cooperatively to effectively promote chemical conversions behaving like nanosized assembly lines. The students will be trained in the synthesis and characterization of hybrid mesoporous materials. They will use a series of analytical methods including powder x-ray diffraction, gas physi- and chemisorption and spectroscopy. Prior experience with any of the mentioned techniques is desirable, but not required, as training will be provided as needed.

Research area:  Nanoscience
Mentor:  Igor Slowing

Catalytic decontamination of water

The project is aimed at removing contaminants from waste water and turning them into useful products. The student will learn methods to produce, characterize and apply nanostructured catalytically active adsorbents. Techniques will include but will not be limited to x-ray diffraction, spectroscopies and chromatography.

Research area: Environmental Sciences
Mentor:  Igor Slowing

Computational Methods for Assembly of Nanoparticles

We develop computational predictions of the assembly of nanoparticles into arrangements with long range order (=superlattices) by different methods strategies: hydrogen bonding, solving evaporation, and others.  We develop methods for structure prediction and materials properties. We use statistical mechanics, molecular dynamics and machine learning. We are also interested in developing code. Knowledge in Python is highly desirable, but not necessary.

Research area:  Nanoscience
Mentor:  Alex Travesset

Bacterial cell-cell communication in the rhizosphere

The rhizosphere represents a critical interface between plant roots and the surrounding soil, harboring a microbial community mediating carbon and nitrogen transformations essential for sequestering carbon and for agricultural productivity. We are interested in developing a deeper understanding of how plants interact with beneficial microbes in the rhizosphere. To establish a root-associated microbiome requires the ability of microbes to communicate with each other by chemical signals that they secrete. These include molecules referred to as quorum-sensing signals that can be either species-specific or universal languages. This project will explore the ability of a newly developed instrument for detecting these molecules produced by microbes. This devise relies on nucleic acid-based sensors integrated into a nanoporous, alumina membrane platform to send signals to a computer to render a 3D image of the distribution of targeted chemicals around the root over time (4D). We will develop a synthetic community that produces these signals or other metabolites that will be detected by the sensor. Through a “plug-and-play” synthetic microbial community we will also be able to introduce signal consumers and other microbes increase community complexity to assess how signal production influence fitness (growth and competitiveness), including identifying underlying mechanisms contributing to fitness. The rhizosphere represents a critical interface between plant roots and the surrounding soil, harboring a microbial community mediating carbon and nitrogen transformations essential for sequestering carbon and for agricultural productivity. We are interested in developing a deeper understanding of how plants interact with beneficial microbes in the rhizosphere. To establish a root-associated microbiome requires the ability of microbes to communicate with each other by chemical signals that they secrete. These include molecules referred to as quorum-sensing signals that can be either species-specific or universal languages. This project will explore the ability of a newly developed instrument for detecting these molecules produced by microbes. This devise relies on nucleic acid-based sensors integrated into a nanoporous, alumina membrane platform to send signals to a computer to render a 3D image of the distribution of targeted chemicals around the root over time (4D). We will develop a synthetic community that produces these signals or other metabolites that will be detected by the sensor. Through a “plug-and-play” synthetic microbial community we will also be able to introduce signal consumers and other microbes increase community complexity to assess how signal production influence fitness (growth and competitiveness), including identifying underlying mechanisms contributing to fitness.

Research area:  Molecular Biology
Mentor:  Larry Halverson

Synthetic Microbial Communities for Exploring Plant-Microbe Interactions

We are interested in developing a deeper understanding of how plants interact with both beneficial and detrimental microbes in the rhizosphere. The rhizosphere represents a critical interface between plant roots and the surrounding soil, harboring a microbial community mediating carbon and nitrogen transformations essential for sequestering carbon and for agricultural productivity. This microbiome produces a suite of chemicals that facilitate not only interactions with other microbes but also with plants themselves. This project will build a testbed for a new instrument for detecting specific molecules produced by microbes or the plant in the rhizosphere. These nucleic acid-based sensors integrated into a nanoporous, alumina membrane platform will send signals to a computer to render a 3D image of the distribution of targeted chemicals around the root over time (4D). Our contribution is to develop a synthetic microbial community for assessing the efficacy of our imaging system while providing insight into the dynamics and fate of the targeted chemicals in the rhizosphere. We will develop synthetic biology tools for controlling production of targeted metabolites by one microbe and separate tools for detecting targeted metabolites by another. Through the construction of a “plug-and-play” synthetic community modelled on the natural maize rhizosphere microbiome, we will increase community complexity, including the introduction of natural producers and consumers of the targeted metabolites.

Research area: Molecular Biology
Mentor:  Larry Halverson

Dynamic NMR Investigation of Supported Scandium Complexes

Single-site supported metal complexes are often seen as a bridge between homogeneous and heterogeneous catalysis fields.  Their selectivity and activity can often be tuned by varying the structure of the ligands, in principle providing a path towards the purpose-driven design of catalysts, and their immobilization onto solid supports allows for the easy separation of the catalyst. Despite this little is known as to their precise atomic-level structures and even less is known about their structural dynamics. In this project we will use NMR spectroscopy to observe the dynamics of supported scandium complexes and determine how these are affected by structural features such as the steric bulk of the ligands, and the topology of the support. The undergraduate student working on this project will be tasked with the synthesis of isotopically-enriched scandium complexes and grafting them onto oxide supports for further analysis via NMR. This internship will provide experience in a synthetic organic and inorganic chemistry laboratory as well as in the use of state-of-the-art solid-state NMR spectroscopy.

Research area:  Inorganic Chemistry
Mentor:  Frederic Perras

Simulations of dilute magnetic structures

The student will use cluster computer to simulate magnetic properties of topological insulators (Tis) that are minutely doped with magnetic elements (Mn, Cr, Fe). The goal of the study is to determine the energy scale and the nature of the magnetic interactions of the doped elements in the TIs. Good computing skills using Matlab, Python (Anaconda, Jupyter), plotting routines are desired.

Research area:  Condensed Matter Physics
Mentor:  David Vaknin

Self-assembly and crystallization of nano-particles

We modify the surfaces of nano-particles by ligand exchange to promote specific interactions that can invoke self-assembly and crystallization of nano-particles into two- and three-dimensional crystals. The long-term goal is to produce so called meta-materials. We use various X-ray diffraction and spectroscopy techniques to determine the structures of the assemblies. The student will be involved in all facets of the project including analysis. Students with background in physics and chemistry with aspirations in materials science will benefit from our lab work. Basic knowledge of Python or any other language will be helpful

Research area:  Nanoscience
Mentor:  David Vaknin

Quantitative analysis of atomic columns in materials

Modern aberration-corrected transmission electron microscopy (TEM) and multifunctional detectors provide an unprecedented opportunity to study atom arrangement and chemistry in materials with sub angstrom resolution. With growing data size and complexity, a computational-aided analysis is crucial to extract property-related structural information. This research project will focus on developing and implementing computer-aided quantitative analysis methods for quantum materials. The student will be involved in developing codes for analyzing and interpreting results for the Superconducting Quantum Materials and Systems Center (SQMS). Knowledge of Python is required.     

Research area:  Condensed Matter Physics
Mentor:  Lin Zhou

Investigation of Caloric Refrigeration Concepts

Caloric materials change temperature in response to externally applied fields (magnetic, stress, electric) and are very promising for replacing conventional vapor-compression systems in cooling applications. Caloric refrigeration has the potential to improve efficiencies while also eliminating the risk of leakage inherent to gaseous refrigerants. Our team at Ames Laboratory has been instrumental in driving the advance of caloric technologies for cooling. The research project will focus on demonstrating early-stage cooling concepts using magnetocaloric and elastocaloric materials.

Research area:  Engineering Mechanical
Mentor:  Julie Slaughter

Develop Dy-free Nd-Fe-B permanent magnets with high temperature stability

Rare earth (RE)-based Nd-Fe-B permanent magnets are used in most of these applications due to their high potential maximum energy product ((BH)max~59 MGOe) at room temperature. However, Nd-Fe-B magnets have poor thermal stability. A heavy rare earth element, Dy or Tb, has to be added to the magnets to enhance the coercivity and improve the thermal stability. The operating temperature of the magnets directly depends on the amount of Dy added. Unfortunately, Dy is expensive and scarce. It was considered as the #1 critical material by the U.S. Department of Energy in 2011 and remains critical today. The supply risks of Nd, Dy, and other RE has stimulated studies for Dy-lean or Dy-free Nd-Fe-B permanent magnets with sufficient energy density and thermal stability for high-performance electric motors and generators. This project is to develop Dy-free Nd-Fe-B magnets with high thermal stability by controlling the magnet's composition and microstructure.

Research area:  Materials Sciences
Mentor:  Wei Tang

 

Develop rare-earth free MnBi magnet for the radiation shielding of nuclear energy applications

Nuclear shielding is a growing market likely to become extremely important in the face of rising global interest in decarbonization. The ability to rapidly install and remove radiation shielding in the field enhances safety while simultaneously adding to worker efficiency. Current magnetic radiation shielding employs Nd-Fe-B (Nd2Fe14B) based magnets.  However, they are largely limited to operational temperatures below ~150 °C and their performance drops rapidly above this temperature.  MnBi is not as strong as Nd-Fe-B at room temperature, but it retains a greater fraction of its remanence to higher temperatures and remains viable as a permanent magnet to over 225 °C. There is a growing market for radiation shielding for use at higher temperatures.

Ames Lab will develop high-performance MnBi magnet and provide it to another DOE Lab (LLNL).  MnBi will be combined with the LLNL’s innovative magnetic designs to develop new and portable radiation shielding.

Research area:  Materials Sciences
Mentor:  Wei Tang

Electronic structure of rare earth materials

The rare-earth metals are becoming increasingly applicable in our everyday life. The enormous importance of rare-earths in the technology, environment, and economy is attracting scientists all over the world to investigate them starting from the extraction to the physical and chemical properties measurements.  Although a lot of works have been done on the experimentation of rare-earths, the true understanding from theory and modeling on these materials is lagging behind. Here, we propose to perform systematic theoretical research from the density functional theory applicable to rare-earths and also study suitable models in order to compare their finite temperature properties obtained from precise experiments.

Research area:  Materials Sciences

Mentor:  Durga Paudyal

Prediction of new materials and properties using machine learning (ML) approaches

The screening of novel materials with good performance and the modelling of quantitative structure-property relationships, among other issues, are hot topics in the field of materials science. Traditional computational modelling often consumes tremendous time and resources and are limited by their theoretical foundations. Thus, it is imperative to develop a new method of accelerating the discovery and design process for novel materials. Recently, materials discovery and design using machine learning have been receiving increasing attention and have achieved great improvements in both time efficiency and prediction accuracy. Here we intend to introduce machine learning for rare earth containing materials, propose possible algorithms to predict new materials. By directly combining computational studies with available experimental data, we hope to provide insight into the parameters that affect the properties of materials, thereby enabling more efficient and target oriented research on materials discovery and design.

Research area: Materials Sciences

Mentor:  Durga Paudyal

Quantum Computing

As quantum information science (QIS) develops quantum computing architectures and storage, security approaches will be required to create trusted platforms and execution environments. QIS can be applied to near term utilization for security applications as well as evaluating future quantum architectures that would not be susceptible to classical computing vulnerabilities. This project aims to collect the current state of simulation/emulation environments including cloud services, cyber-security for quantum computing, and cyber-security utilizing quantum algorithms. This project would then create a framework for further quantum applications, document and create a development environment (e.g. python, QISKIT, etc.) and demonstrate a quantum algorithm for a cyber-security application such as random number or quantum key generation.

Research area: Materials Sciences

Mentor:  Durga Paudyal

Ordered Intermetallic Compounds for Heterogeneous Catalysis

Precious metals and metal alloys are important heterogeneous catalysts for renewable
energies and materials. However, both of them have their limitations. Precious metals
have low natural abundance and are expensive. Metal alloys have unstable surfaces
due to surface segregation under reaction conditions, which renders the identification of
active sites and the understanding of reaction mechanisms difficult. My research group
will address these limitations by developing new intermetallic NP catalysts. Intermetallic
compounds, which consist of two or more metallic elements, adopt
specific crystal structures as well as electronic structures different from the constituent
elements. The modified electronic structures of intermetallic compounds make them
unique catalytic materials. It has been proposed that such compounds should be treated
as new “elements”, considering their potential in catalysis. The inherent properties of
intermetallic compounds, stable and exhibit a large variety of structures, will help us to
discover catalysts with stable surfaces, consisting of more abundant metals, to replace
unstable alloy and precious metal catalysts.
Research area: Inorganic Chemistry
Mentor: Wenyu Huang

Developing Functionalized Graphene for Biomass Conversion

The goal of this research is to develop low-cost catalysts based on graphene-derived
nanomaterials and use them to improve the efficiency of several key steps in biomass
refinery. To make the cost of biomass-derived fuels comparable, or lower than that of
petroleum fuels, it is necessary to develop new catalysts and processes that can
substantially improve the efficiency of biomass refinery. Two attractive biomass refinery
processes, pyrolysis, and hydrolysis of lignocellulose, usually give molecules containing
high oxygen content, and thus low energy density to be used directly as fuel. Therefore,
upgrading of the lignocellulose derived oxygenates is necessary for them to be fit into
appropriate fuel classes (i.e., gasoline, diesel, or jet fuels). The general approaches for
upgrading the oxygenates are to decrease their oxygen contents, and to build carbon-
carbon bonds, targeting different fuel classes. Catalysts play a vital role in converting
and upgrading biomass to fuels, and thus need to be studied extensively. Catalysts
based on graphene-derived nanomaterials could greatly improve the efficiency of
biomass conversion and substantially decrease the cost of biomass conversion.    

Research area: Renewable Energy Sciences and Technologies
Mentor: Wenyu Huang

Control heterogeneous catalysis at atomic and electronic-level using metal-organic
frameworks

To control heterogeneous catalysis at atomic and electronic-level represents one of the
most challenge research areas. Using metal-organic frameworks (MOFs) as hosts of
metal nanoclusters, we could reach an atomic and electronic-level control of
heterogeneous catalysts. MOFs, as novel template materials for the synthesis of metal
nanoclusters, have great potentials for catalysis due to their structural diversity,
flexibility, and tailorability, as well as high porosity. Compared to zeolite, the chemical
environment of each cage/cavity of MOFs can be controlled at the atomic-level by using
different organic linkers. The MOFs with isoreticular structures are particularly
interesting because they have exactly the same lattice structure, but different chemical
compositions. These different organic linkers or metal ion nodes of MOFs result in
geometrically identical cages of different chemical environments. Nanoclusters,
confined in these cages/cavities, would experience an atomic-level fine-tuned chemical
environment, and thus exhibit different activity and selectivity in heterogeneous
catalysis. During chemical conversion processes, reactants and reaction intermediates
could also sense these chemical environments that could alter their adsorption energy
and geometry, which will also affect the reaction activity and selectivity.
Research area: Nanoscience
Mentor: Wenyu Huang

Chiral Catalysis Using Surface-Engineered Heterogeneous Catalysts

Chirality, an essential attribute of nature, engenders unique pharmacological and
biological properties in a great variety of substances. However, the synthesis of chiral
molecules presents a unique challenge in catalysis. The potential to exhibit selectivity
beyond the standard structure is particularly challenging and requires a specifically
tuned catalyst to perform. This project will seek to perform this by modifying already
chemoselective heterogeneous catalysts by impregnating the support with chiral
modifiers. There are several potential heterogeneous catalysts to test, but an ideal case
would be one in which the chiral modifiers adsorb to a specific type of active site while
leaving another exposed. This would potentially force the reaction to produce only one

of the possible stereoisomers rather than a racemic mixture. Potential reactions for this
system include C=O hydrogenation for acetophenone or methyl pyruvate.
Research area: Physical Chemistry
Mentor: Wenyu Huang

Tuning Magnetic Ordering in Magnetic Materials Containing Rare Earths

The rare earths materials play an increasingly important role in modern technology. Among them, magnetic intermetallic alloys and compounds containing lanthanides are known for their both current (permanent magnets, magnetic actuators) and future (near room temperature magnetic cooling, quantum information) technologies. The proposed experimental research focuses on magnetic rare earth alloys, in particular on the optimization and control of their magnetic ordering. In our fundamental research we are exploring non-trivial approaches, such as, for example, enhancement of magnetic ordering temperature using chemical substitution of highly magnetic atoms (Gd, Tb, Dy) by non-magnetic atoms (e.g. Sc, Ti).  We are looking for candidates interested in performing experimental synthesis (via melting and heat treatment) and basic characterization (X-ray powder diffraction and magnetic measurements) of ternary
and quaternary intermetallic compounds containing one or more rare earth element. The
anticipated outcome is a publication in a peer-reviewed science journal.
Research area: Materials Sciences
Mentor: Yaroslav Mudryk

Defining the principles of aptamer-ligand interaction to improve aptamer affinity and specificity

Nucleic acid aptamers are proving to be extremely useful elements in sensors to detect identified targets such as proteins and small molecules. Obtaining aptamers starts with a pool of about 10^15 oligonucleotides that are selected by a repetitive process of 6-12 rounds of capture and amplification. The resulting oligonucleotide pool is then evaluated by informatics and likely aptamers are identified for further analysis. The best of these chosen aptamers are incorporated into sensors for detecting the target molecule. However, sensors must be both sensitive to the target molecule (analyte) and specific for that analyte over others. Although the selection protocol is effective in isolating aptamers with high affinity for the identified target, it has limited ability to select against alternate, potentially interfering molecules. Thus, it is important to understand how an aptamer interacts with its target and be able to predict interaction with interfering molecules or to change the structure/sequence of the aptamer to give it higher affinity or to make it more specific for its target molecule. To explore approaches to understanding aptamer-target interaction with the purpose of improving aptamer affinity and specificity, we are using a combined experimental and computational approach.

Research area: Molecular Biology
Mentor:  Marit Nilsen-Hamilton

Building an aptasensor to detect the SARS CoV-2 virus

In this period of COVID-19, it is essential that we develop fast and reliable tests for the virus that is causing this pandemic. This project is to build the parts of a new instrument for sensing specific molecules on viruses. The part we are focusing on first is to build the sensors that will be used to detect the virus particles. These sensors rely on aptamers to recognize the virus. Aptamers are nucleic acids that, like antibodies, specifically recognize a target protein or virus particle. However, unlike antibodies, aptamers can be selected in vitro and synthesized chemically. When aptamers are the means of detecting the virus the sensor is called an aptasensor. An aptasensor is being developed that will detect SARS CoV-2 virus particles and send signals to a central computer which converts the signal to a measure of the presence or absence of the virus. To build the sensors we will be using nucleic acid aptamers that specifically recognize the SARS CoV-2 virus. Compared with antibodies, aptamers have properties that are much more applicable to functioning on a range of sensor platforms. The aptamers will be integrated into a nanoporous anodized aluminum oxide sensing platform to create an aptasensor for detecting the virus presence. This aptasensor will be inexpensive and not require refrigeration and thus could be stored for long periods before it is used. It will also be easy to use and so can be used in remote areas of the country outside of hospital laboratories.

Research area:  Engineering Biological (nonmedical)
Mentor:  Marit Nilsen-Hamilton

Quantum computing algorithms for simulations of quantum materials

In this SULI, you will participate in our group's efforts to develop and apply quantum algorithms for simulating the behavior of quantum materials. Predicting the properties of real materials can guide experimental design efforts towards a wide variety of applications in energy and information sciences. As part of a national Department of Energy quantum center "Superconducting Quantum Materials and Systems" (SQMS), this project focuses on the development and implementation of hybrid quantum-classical algorithms that can be run on state-of-the-art superconducting quantum processing units (QPU) of our SQMS partner Rigetti Computing. The goal of this project is to implement algorithms using the quantum computing language PyQuil and benchmark their performance on Rigetti QPUs using modern error mitigation protocols. The algorithms will be used to simulate the non-equilibrium dynamics of quantum materials, in particular, their nonlinear electromagnetic response in the presence of a strong coherent laser field. 

Research area:  Condensed Matter Physics
Mentor:  Peter Orth

Exploring gate-tunable polariton transport in 2D semiconductors

Exciton polaritons are quasiparticles generated due to the coherent coupling between photons and excitons in semiconductors. The strong light-matter interactions and the bosonic nature of exciton polaritons have led to many groundbreaking discoveries such as Bose-Einstein condensation, polariton superfluidity, and polariton lasing. In recent years, exciton polaritons were studied extensively in group VI transition-metal dichalcogenides (TMDs) with chemical formula MX2 (M = Mo, W; X = S, Se) – a class of van der Waals two-dimensional (2D) semiconductors. It was found that exciton polaritons in this class of materials are stable at ambient conditions and cover a wide spectral range from near-infrared to visible frequencies can be tailored by controlling the sample thickness with atomic accuracy. Nevertheless, gate tunability of exciton polariton transport, which is essential for the realization of tunable polaritonic devices (e.g., polariton transistors and polariton modulators) in future nanophotonic circuits, has not been realized yet.

In this project, we propose to explore gate-tunable polariton transport in TMDs by using the state-of-the-art scattering-type scanning near-field optical microscopy (s-SNOM). The objectives of this research are: (1) to fabricate gate-tunable TMD devices; (2) to image the propagative polaritons with s-SNOM; (3) to realize practical polariton devices. The proposed research will deepen our understanding of the nano-optical and nano-electronic physics of these 2D semiconductors, revolutionize our approach towards tunable nanophotonics in the technologically important near-infrared to visible regions, and establish TMD atomic layers as novel materials that are promising for coherent nanophotonic applications in optical communications and data processing with broad bandwidth and active controllability.

Research area:  Atomic, Molecular, and Optical Sciences
Mentor:  Zhe Fei

Modeling of self-assembly and reaction-diffusion processes far-from-equilibrium

Physical and chemical processes occurring far-from-equilibrium can exhibit an extraordinarily rich variety of spatio-temporal behavior (development of complex morphologies for self-assembly of nanoscale materials, non-linear kinetics or dynamics, wave propagation and pattern formation in reaction-diffusion systems). This behavior is the result of the cooperative interaction between large numbers of atoms or molecules. We attempt to model this behavior at the atomistic level. Conventional Molecular Dynamics simulations (just integrating Newton's equations) cannot describe the behavior of interest on the relevant time scales. Thus, we instead use 'stochastic models' just tracking atom positions, and implementing various relevant processes or moves with probabilities which reflect the physical rates for such processes (e.g., adsorption, desorption, diffusion, and reaction for processes occurring at surfaces). The models are analyzed by Kinetic Monte Caro simulation, but also by analytical mathematical methods. Familiarity with Mathematica or Matlab, and ideally with coding in other languages, is particularly valuable.

Research area:  Nanoscience
Mentor:  Jim Evans

Exploration of Complex Metal Pnictides Containing Refractory Metalloids, Carbon and Boron

The project will investigate ternary and quaternary intermetallics containing tetrels (Si, Ge, Sn) or refractory metalloid (B, C) and pnictogen (P, As, Sb, Bi) or chalcogen (S, Se, Te). A novel synthetic approach will be developed by binding metals and metalloids in one compounds and than reacting it with volatile pnictogen. Novel phases will be synthesized with unique crystal structures due to flexibility provided by the presence of two non-metal elements able to form strong covalent bonds. Presence of transition and rare-earth metal will provide local magnetic moments and strong spin-orbit coupling which will result in exciting magnetic and transport properties. Properties tunability will be the main focus to realize quantum materials based on the proposed objects of study. Using computational input, the stability of such quaternary phases for second and third row transition metals, as well as systems contaning boron and carbon will be investigated. The mechanism of the synthesis will also be explored.

Research area:  Materials Sciences
Mentor:  Georgiy Akopov

4DMAPS: Portable sensors for monitoring rhizosphere

Project will address the challenge of monitoring the physiology and inteactions of plants with other organisms in soil and their responses to the chemical and microbial composition of the rhizosphere. We will develop a network of aptamer functionalized sensors to monitor the chemicals excreted by plant roots and their interactions with surrounding soil. The students will design, fabricate and characterize sensors that will be used in the soil monitoring.
Nanoporous alumina membranes have become a ubiquitous biosensing platform for a
variety of applications and aptamers are being increasingly utilized as recognition elements in protein sensing devices. Combining the advantages of the two, we will utilize the aptamer functionalized alumina membranes for label-free sensitive detection of small molecules using a four-electrode electrochemical cell. An arduino based reader will be developed to monitor the impedance of the alumina membrane in the four electrode cell configuration.
Research area: Engineering Mechanical
Mentor: Pranav Shrotriya

Optical and Microscopy Characterizations of Transmon Quantum Bits

A grand challenge underlying quantum information science (QIS) applications is how to characterize microstructures of transmon qubits and increase coherence time. Pushing the state-of-art requires visionary experiments and versatile tools, particularly, at space-time limit of deep-subwavelength (<100 nm) scales and microwave/terahertz frequencies. The project aims to apply various microscopy and nano-photonics tools to study transmon quantum bits at the space-time limit.  The dynamic and coherent processes to be demonstrated include conductivity imaging, tunneling junction characterizations, supercurrent control.

These align well to four Priority Research Opportunities (PROs) identified in the BES report “Opportunities for Basic Research for Next-Generation Quantum Systems”.  Our research involves quantum control and sensing directly targeting quantum information functionality, and probing and understanding of foundational phenomena using optics and micorospcy methods. Our success will provide unprecedented quantum control and imaging capabilities “never-before-accessible” for communities of condensed matter/materials, photonics and quantum control/information science. 

This work was supported by the Ames Laboratory, the US Department of Energy, Office of Science, Basic Energy Sciences, Materials Science and Engineering Division under contract No. DEAC02- 07CH11358, and by Superconducting Quantum Materials and Systems Center, an National QIS Center funded by the U.S. DOE, Office of Basic Energy Sciences.

Research area: Condensed Matter Physics
Mentor:  Jigang Wang

Spring 2021

Quantitative visualization of atom movement in materials

Modern transmission electron microscopy (TEM) and multifunctional detectors provide an unprecedented opportunity to study the phase transition process at the atomic scale in materials under external stimuli, such as temperature, magnetic field, and stress. With growing data size and complexity in multidimensionality, a computational-aided analysis is crucial to extract structural evolution information. This research project will focus on developing image-based quantitative analysis methods from TEM images of various materials, including magnetic materials, metals, and ceramics. The student will be involved in developing codes for analyzing and interpreting results. The knowledge of Python is required.     

Research area:  Materials Sciences
Mentor:  Lin Zhou

 

Ordered Intermetallic Compounds for Heterogeneous Catalysis

Precious metals and metal alloys are important heterogeneous catalysts for renewable energies and materials. However, both of them have their limitations. Precious metals have low natural abundance and are expensive. Metal alloys have unstable surfaces due to surface segregation under reaction conditions, which renders the identification of active sites and the understanding of reaction mechanisms difficult. My research group will address these limitations by developing new intermetallic NP catalysts. Intermetallic compounds, which consist of two or more metallic elements, adopt specific crystal structures as well as electronic structures different from the constituent elements. The modified electronic structures of intermetallic compounds make them unique catalytic materials. It has been proposed that such compounds should be treated as new “elements”, considering their potential in catalysis. The inherent properties of intermetallic compounds, stable and exhibit a large variety of structures, will help us to discover catalysts with stable surfaces, consisting of more abundant metals, to replace unstable alloy and precious metal catalysts.

Research area:  Nanoscience
Mentor:  Wenyu Huang

 

Control heterogeneous catalysis at atomic and electronic-level using metal-organic frameworks

To control heterogeneous catalysis at atomic and electronic-level represents one of the most challenge research areas. Using metal-organic frameworks (MOFs) as hosts of metal nanoclusters, we could reach an atomic and electronic-level control of heterogeneous catalysts. MOFs, as novel template materials for the synthesis of metal nanoclusters, have great potentials for catalysis due to their structural diversity, flexibility, and tailorability, as well as high porosity. Compared to zeolite, the chemical environment of each cage/cavity of MOFs can be controlled at the atomic-level by using different organic linkers. The MOFs with isoreticular structures are particularly interesting because they have exactly the same lattice structure, but different chemical compositions. These different organic linkers or metal ion nodes of MOFs result in geometrically identical cages of different chemical environments. Nanoclusters, confined in these cages/cavities, would experience an atomic-level fine-tuned chemical environment, and thus exhibit different activity and selectivity in heterogeneous catalysis. During chemical conversion processes, reactants and reaction intermediates could also sense these chemical environments that could alter their adsorption energy and geometry, which will also affect the reaction activity and selectivity.

Research area: Inorganic Chemistry
Mentor:  Wenyu Huang

Prediction of new materials and properties using machine learning (ML) approaches

Prediction of new materials and properties using machine learning (ML) approaches
The screening of novel materials with good performance and the modelling of quantitative structure-property relationships, among other issues, are hot topics in the field of materials science. Traditional computational modelling often consume tremendous time and resources and are limited by their theoretical foundations. Thus, it is imperative to develop a new method of accelerating the discovery and design process for novel materials. Recently, materials discovery and design using machine learning have been receiving increasing attention and have achieved great improvements in both time efficiency and prediction accuracy. Here we intend to introduce machine learning for rare earth containing materials, propose possible algorithms to predict new materials. By directly combining computational studies with available experimental data, we hope to provide insight into the parameters that affect the properties of materials, thereby enabling more efficient and target oriented research on materials discovery and design.

Research area:  Materials Sciences
Mentor:  Durga Paudyal

Electronic structure of rare earth materials

The rare-earth metals are becoming increasingly applicable in our everyday life. The enormous importance of rare-earths in the technology, environment, and economy is attracting scientists all over the world to investigate them starting from the extraction to the physical and chemical properties measurements.  Although a lot of works have been done on the experimentation of rare-earths, the true understanding from theory and modeling on these materials is lagging behind. Here, we propose to perform systematic theoretical research from the density functional theory applicable to rare-earths and also study suitable models in order to compare their finite temperature properties obtained from precise experiments.

Research Area:  Materials Sciences
Mentor:  Durga Paudyal

Synthesis and characterization of complex metal pnictides

Pnictides exhibit a diverse range of properties ranging from thermoelectric materials to high-temperature superconductors. Our research group work on synthesis, structural and properties characterization of novel complex pnictide materials containing transition and/or rare-earth metals. The project will include solid-state synthesis of novel compounds, determination of their crystal structure, and characterization of the electrical and heat transport properties.

Research area:  Materials Sciences
Mentor:  Kirill Kovnir

Investigation of Caloric Refrigeration Concepts

Caloric materials change temperature in response to externally applied fields (magnetic,
stress, electric) and are very promising for replacing conventional vapor-compression
systems in cooling applications. Caloric refrigeration has the potential to improve
efficiencies while also eliminating the risk of leakage inherent to gaseous refrigerants. Our team at Ames Laboratory has been instrumental in driving the advance of caloric
technologies for cooling. The research project will focus on demonstrating early-stage
cooling concepts using magnetocaloric and elastocaloric materials.
Research area: Engineering Mechanical
Mentor: Julie Slaughter

Self assembly and crystallization of nano-particles

We modify the surfaces of nano-particles by ligand exchange to promote specific interactions that can invoke self assembly and crystallization of nano-particles into two- and three-dimensional crystals. The long term goal is to produce so called meta-materials. We use various X-ray diffraction and spectroscopy techniques to determine the structures of the assemblies. The student will be involved in all facets of the project including analysis. Students with background in physics and chemistry with aspirations in materials science will benefit from our lab work. Basic knowledge of Python or any other language will be helpful.

Research area:  Nanoscience
Mentor:  David Vaknin
 

Catalytic Conversion of Carbon Dioxide

Carbon Capture, Utilization and Storage is a highly-sought goal by Department of Energy. We would like to target the catalytic conversion of carbon dioxide to produce value-added oxygenates as advanced fuels and chemicals. 

Highly selective catalysts will be synthesized with first-row transition metals. The metal-based nanoparticles will be supported on an acid-resistant and water-tolerant porous catalyst. A plug-flow reactor will be designed and custom-made, which should be readily scalable. The reactor will be coupled with the fully-automated chromatographic techniques for online analysis. Hydrogen gas will be used as the reducing agents. Reactions of CO2 with epoxides will be studied as well for the production of organic carbonates. In both cases, reaction conditions, including flow rate, temperature, system pressure, etc., will be investigated to evaluate the selectivities of various catalysts in a continuous flow mode. 

Research area:  Physical Chemistry
Mentor:  Long Qi

Data Science for Catalysis

Data science has drastically changed how data are collected and analyzed. We would like to introduce new methodologies in data science into catalysis science, which is the key in petroleum refinery and pharmaceutical industries. 

In this project, new methods including simulation and modeling, and machine learning will be developed and implemented to increase the instrument efficiency and understand more of the experimental data. 

Research area:  Physical Chemistry
Mentor:  Long Qi

Defining the principles of aptamer-ligand interaction to improve aptamer affinity and specificity

Nucleic acid aptamers are proving to be extremely useful elements in sensors to detect identified targets such as proteins and small molecules. Obtaining aptamers starts with a pool of about 1015oligonucleotides that are selected by a repetitive process of 6-12 rounds of capture and amplification. The resulting oligonucleotide pool is then evaluated by informatics and likely aptamers are identified for further analysis. The best of these chosen aptamers are incorporated into sensors for detecting the target molecule. However, sensors must be both sensitive to the target molecule (analyte) and specific for that analyte over others. Although the selection protocol is effective in isolating aptamers with high affinity for the identified target, it has limited ability to select against alternate, potentially interfering molecules. Thus, it is important to understand how an aptamer interacts with its target and be able to predict interaction with interfering molecules or to change the structure/sequence of the aptamer to give it higher affinity or to make it more specific for its target molecule. To explore approaches to understanding aptamer-target interaction with the purpose of improving aptamer affinity and specificity, we are using a combined experimental and computational approach.

Research area: Molecular Biology
Mentor:  Marit Nilsen-Hamilton

Bacterial cell-cell and bacterial-plant interactions in the rhizosphere

The rhizosphere represents a critical interface between plant roots and the surrounding soil, harboring a microbial community mediating carbon and nitrogen transformations essential for sequestering carbon and for agricultural productivity.   This microbiome produces a suite of chemicals that facilitate not only interactions with other microbes but also with plants themselves. Many of these molecules can stimulate or inhibit bacterial or even plant growth.  To establish a root-associated microbiome requires the ability of microbes to communicate with each other by chemical signals that they secrete. This project will explore the ability of a newly developed instrument for detecting these molecules produced by microbes. This devise relies on nucleic acid-based sensors integrated into a nanoporous, alumina membrane platform to send signals to a computer to render a 3D image of the distribution of targeted chemicals around the root over time (4D).  We will develop a synthetic community that produces these signals or other metabolites that will be detected by the sensor.  Through a “plug-and-play” synthetic microbial community we will also be able to introduce signal consumers and assess how signal production influence fitness (growth and competitiveness), including identifying underlying mechanisms contributing to fitness.

Research area:  Engineering Biological (nonmedical)
Mentor:  Larry Halverson

Fall 2020

Plastic Upcycling Through Chemical Catalysis

We are developing catalysts for conversion of polymers, the principle component in plastics, from waste materials into new polymers, monomers for repolymerization (recycling), or new valuable chemicals. The vision is that such chemical transformations will provide incentives for collection and processing of plastic waste, which currently are landfilled or discarded one hundred megaton scale. Our approach involves synthesis of supported catalysts and investigation of reactions that break the carbon-carbon bonds polymer chain backbones.

Research area: Inorganic Chemistry

Mentor: Aaron Sadow

Quantitative visualization of atomic columns in materials

Modern aberration-corrected transmission electron microscopy (TEM) and multifunctional detectors provide an unprecedented opportunity to study atom arrangement and chemistry in materials with sub angstrom resolution. With growing data size and complexity, a computational-aided analysis is crucial to extract property-related structural information. This research project will focus on developing atomic-scale image-based quantitative analysis methods for various material systems, including topological magnetic materials and ferroelectric oxides. The student will be involved in developing codes for analyzing and interpreting of results. The knowledge of Python or similar programing language is required.

Which of the following Research Areas is best aligned with this proposed project?

Research area: Materials Sciences
Mentor:  Lin Zhou

 

Chiral Catalysis Using Specially Heterogeneous Catalysts

Chirality, an essential attribute of nature, engenders unique pharmacological and biological properties in a great variety of substances. However, the synthesis of chiral molecules presents a unique challenge in catalysis. The potential to exhibit selectivity beyond the standard structure is particularly challenging and requires a specifically tuned catalyst to perform. This project will seek to perform this by modifying already chemoselective heterogeneous catalysts by impregnating the support with chiral modifiers. There are several potential heterogeneous catalysts to test, but an ideal case would be one in which the chiral modifiers adsorb to a specific type of active site while leaving another exposed. This would potentially force the reaction to produce only one of the possible stereoisomers rather than a racemic mixture. Potential reactions for this system include C=O hydrogenation for acetophenone or methyl pyruvate.

Research area:  Nanoscience
Mentor:  Wenyu Huang

 

Heterogeneous Rare-earth Permanent Magnets with Enhanced Mechanical Properties

Rare-earth permanent magnets (REPMs) have excellent magnetic properties and have been widely used in energy conversion and storage, telecommunication, consumer electronics, biomedical devices, and magnetic sensors. However, REPMs are brittle and cannot be used for applications subjected to high stress, vibration or mechanical shock. The brittleness also leads to the magnet production loss up to 20-30% in volume and imposes limitations on part size and shape. This project is to produce REPMs (mainly Sm-Co and Nd-Fe-B sintered magnets) mechanically and magnetically stronger than the commercial products while reducing magnet waste rate to less than 10%. The novel magnets will be more cost-effective, efficient and robust for energy-related applications while reducing the pressure on critical material supply chain.

 

Research area:  Materials Science
Mentor:  Baozhi Cui

High Performance Permanent Magnets for Energy Applications

Permanent magnets are increasingly ubiquitous in many applications but are reliant upon expensive rare earth elements which must be obtained from foreign sources. The high cost of expensive rare earth elements is already a threat to technological advancement. Disruption in the supply of these rare earth elements will hinder progress in high-tech and clean energy technologies including wind energy, magnetic resonance imaging, data storage, electric vehicles and many more. As a result, there are global technological and energy security needs to make permanent magnets with reduced or without rare earth elements. This research will enable students to gain hands-on experience on making powerful permanent magnets. Students will be exposed to our state of the art research equipment for production and testing of magnetic properties. The proposed project will focus mainly on making magnets with reduced or no critical rare earth elements. The student will use our new Controlled Atmosphere Materials Processing System for the research.As part of the Critical Materials Institute, students will have the opportunity to observe a multi-institutional research project designed to strategically support the competitiveness of the United States in clean energy technologies.
 

Research area: Materials Science
Mentor: Ikenna Nlebedim

Summer 2020

Synthetic Microbiomes for Exploring Plant-Microbe Interactions

We are interested in developing a deeper understanding of how plants interact with both beneficial and detrimental microbes in the rhizosphere.  The rhizosphere represents a critical interface between plant roots and the surrounding soil, harboring a microbial community mediating carbon and nitrogen transformations essential for sequestering carbon and for agricultural productivity.   This microbiome produces a suite of chemicals that facilitate not only interactions with other microbes but also with plants themselves. This project will build a test-bed for a new instrument for detecting specific molecules produced by microbes or the plant in the rhizosphere.  These nucleic acid-based sensors integrated into a nanoporous, alumina membrane platform will send signals to a computer to render a 3D image of the distribution of targeted chemicals around the root over time (4D). Our contribution is to develop a synthetic microbial community for assessing the efficacy of our imaging system while providing insight into the dynamics and fate of the targeted chemicals in the rhizosphere. We will develop synthetic biology tools for controlling production of targeted metabolites by one microbe and separate tools for detecting targeted metabolites by another.  Through the construction of a “plug-and-play” synthetic community modeled on the natural maize rhizosphere microbiome, we will increase community complexity, including the introduction of natural producers and consumers of the targeted metabolites.

Research area: Engineering Biological (nonmedical)
Mentor:  Larry Halverson

Ordered Intermetallic Compounds for Heterogeneous Catalysis

Precious metals and metal alloys are important heterogeneous catalysts for renewable energies and materials. However, both of them have their limitations. Precious metals have low natural abundance and are expensive. Metal alloys have unstable surfaces due to surface segregation under reaction conditions, which renders the identification of active sites and the understanding of reaction mechanisms difficult. My research group will address these limitations by developing new intermetallic NP catalysts. Intermetallic compounds, which consist of two or more metallic elements, adopt specific crystal structures as well as electronic structures different from the constituent elements. The modified electronic structures of intermetallic compounds make them unique catalytic materials. It has been proposed that such compounds should be treated as new “elements” considering their potential in catalysis. The inherent properties of intermetallic compounds, stable and exhibit a large variety of structures, will help us to discover catalysts with stable surfaces, consisting of more abundant metals, to replace unstable alloy and precious metal catalysts.

Research area:  Materials Sciences
Mentor:  Wenyu Huang

Control heterogeneous catalysis at atomic and electronic-level using metal-organic frameworks

To control heterogeneous catalysis at atomic and electronic-level represents one of the most challenge research areas. Using metal organic frameworks (MOFs) as hosts of metal nanoclusters, we could reach an atomic and electronic-level control of heterogeneous catalysts. MOFs, as novel template materials for the synthesis of metal nanoclusters, have great potentials for catalysis due to their structural diversity, flexibility and tailorability, as well as high porosity. Compared to zeolite, the chemical environment of each cage/cavity of MOFs can be controlled at atomic-level by using different organic linkers. The MOFs with isoreticular structures are particularly interesting because they have exactly the same lattice structure, but different chemical compositions. These different organic linkers or metal ion nodes of MOFs results geometrically identical cages of different chemical environments. Nanoclusters, confined in these cages/cavities, would experience an atomic-level fine-tuned chemical environment, and thus exhibit different activity and selectivity in heterogeneous catalysis. During chemical conversion processes, reactants and reaction intermediates could also sense these chemical environments that could alter their adsorption energy and geometry, which will also affect the reaction activity and selectivity.

Research area:  Nanoscience
Mentor:  Wenyu Huang

Plant/microbe communication with aptamers

The rhizosphere is a thin layer around the roots of a plant where microbes congregate. Some microbes are beneficial and others pathogenic. Plants need microbes in the rhizosphere for their proper nutrition. So, they do things to attract the beneficial microbes. For example, up top 70% of a plant's energy can be excreted through the roots into the surrounding rhizosphere to feed the microbes, some of which convert nitrogen gas into forms like ammonium that can be absorbed by the plant. We are interested in understanding this mutualistic relationship as it occurs in the soil. We are also interested in understanding how plants interact with harmful microbes that sometimes enter the rhizosphere. To gain this understanding, we need to obtain data on the molecular signals by which plants and microbes interact. This project is to build the parts of a new instrument for sensing specific molecules in the rhizosphere. The part we are focusing on first is to build the sensors that will be used to detect the molecules. These sensors will send signals to a central computer which will create a 3D image of the distribution of this chemical around the root over time (4D). To build the sensors we will be selecting and maturing nucleic acid aptamers that specifically recognize the molecules of interest. Similar in their function to antibodies, aptamers have properties that are much more applicable to functioning underground than do antibodies. Once selected and matured, the aptamers will be integrated into a nanoporous anodized aluminum oxide sensing platform to create a sensor that will be placed at the tips of the instrument to be placed in the soil for molecular recognition.

Research area:  Engineering Biological (nonmedical)
Mentor: Marit Nilsen-Hamilton

Design of Physically Motivated Anisotropic Atomic Orbital Basis Sets

The goal of theoretical chemistry is to explain and predict chemical phenomena.  Physically we know that such phenomena are described by the Schrödinger equation (SE); unfortunately, analytic solutions to the SE do not exist for most chemical systems of interest. Nonetheless, it is possible to approximate the SE, to arbitrary accuracy, starting from the familiar linear combination of atomic orbitals (AO) ansatz.  The AOs in this ansatz are numeric approximations to the familiar s, p, d, f, etc. orbitals introduced in general chemistry.  Such AOs are well suited for describing an isolated atom, but poorly describe the anisotropic electronic environments found around atoms in molecular environments.  The goal of this project is to extend the traditional AO basis sets so that the resulting basis sets includes anisotropy. The resulting anisotropic AOs (AAO) are the numeric analogs of the traditional spsp2, sp3, ... hybrid AOs.  Because AAOs better describe the anisotropic electronic environments within molecules, It is anticipated that AAO ansätze for molecular systems will be shorter compared to traditional, similar quality, AO ansätze. Given that the time to approximate the SE scales non-linearly with respect to the number of AOs, this means that AAOs should reduce the time needed to approximate the SE.  Resultantly, AAOs have the potential to extend the domain of chemical systems to which theoretical chemistry is applicable.

Research area:  Theoretical Chemistry
Mentor:  Richard Ryan

Synthesis and characterization of novel pnictide materials

Pnictides exhibit a diverse range of properties ranging from thermoelectric materials to high-temperature superconductors. Our research group work on synthesis, structural and properties characterization of novel complex pnictide materials containing transition and/or rare-earth metals. The project will include solid-state synthesis of novel compounds, determination of their crystal structure, and characterization of the electrical and heat transport properties.

Research area: Materials Sciences
Mentor:  Kirill Kovnir

Prediction of new materials and properties using machine learning (ML) approaches

The screening of novel materials with good performance and the modelling of quantitative structure-property relationships, among other issues, are hot topics in the field of materials science. Traditional computational modelling often consume tremendous time and resources and are limited by their theoretical foundations. Thus, it is imperative to develop a new method of accelerating the discovery and design process for novel materials. Recently, materials discovery and design using machine learning have been receiving increasing attention and have achieved great improvements in both time efficiency and prediction accuracy. Here we intend to introduce machine learning for rare earth containing materials, propose possible algorithms to predict new materials. By directly combining computational studies with available experimental data, we hope to provide insight into the parameters that affect the properties of materials, thereby enabling more efficient and target oriented research on materials discovery and design.

Research area: Engineering Materials
Mentor:  Durga Paudyal

Multifunctional Catalysts based on Zeolites

Zeolites are microporous crystalline materials composed of alumino-silicate or phosphate. Because of the high thermal stability and strong acidobascity, zeolites have been widely applied in refinery industry. Because regular pore morphologies of zeolites to control the diffusion and formation of molecules of different sizes, zeolites are often called molecular sieves. Besides, zeolites have also used as a support to accommodate molecular metal complexes or metal nanoparticles. The resulting materials become bifunctional, bearing both acidobascity of the zeolites and redox activity from the metals.

We would like to apply zeolites as support for molecular organometallic complexes with rare earth metals and early transition metals, using a chemical liquid deposition method (CLD). The metal will bond directly with isolated bridging oxygen sites in the zeolite, resulting in a bifunctional catalyst. The catalyst can retain the microporous structure and enable hydro-treatment of both fossil and biomass resources. The hydrogenation activation and subsequent reactions will be studied with in situspectroscopy including diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and operando high temperature/pressure solid-state NMR.

Research Area: Materials Sciences
Mentor: Long Qi

Development of Quantum Sensors for Quantum Materials Research

Quantum materials such as superconductors and magnetic skyrmions show promise for advanced technologies including energy-efficient electronics, and technologies based on quantum information science (QIS). Realization of such advanced technologies depend on how well we understand fundamental physics of the relevant quantum material. This requires novel methods of sensing and characterization with better sensitivity and minimal effect on the studied system. In other words, quantum materials need quantum methods of sensing.

Here at Ames Laboratory, we develop new techniques to study magnetic and electronic properties of quantum materials. One of them is based on the nitrogen-vacancy (NV) atomic defect in diamond. This “NV-center” can be viewed as an electron “trapped” in diamond crystal and we access quantum energy levels of electron spin to detect the presence of very weak magnetic fields.

The SULI student will learn the techniques of quantum sensing and atomic force microscopy (AFM) and develop multi-disciplinary hands-on skills working with optical, electronic, and microwave networks. Essentially, the student will learn how condensed matter physicist works in the lab, starting from the development and improvement of the experiment, acquisition of scientific data, and to writing research reports potentially resulting in peer-reviewed journals.

Research area:  Condensed Matter Physics
Mentor:  Naufer Nusran

Exploration of Complex Metal Pnictides Containing refractory Metalloids, Boron and Carbon

The project will investigate ternary and quaternary intermetallics containing refractory metalloid (B, C) and pnictogen (P, As, Sb, Bi). A novel synthetic approach will be developed by binding metals and metalloids in one compounds and than reacting it with volatile pnictogen. Novel phases will be synthesized with unique crystal structures due to flexibility provided by the presence of two non-metal elements able to form strong covalent bonds. Presence of transition and rare-earth metal will provide local magnetic moments and strong spin-orbit coupling which will result in exciting magnetic and transport properties. Properties tunability will be the main focus to realize quantum materials based on the proposed objects of study. Using computational input, the stability of such quaternary phases for second and third row transition metals, as well as systems contaning boron and carbon will be investigated. The mechanism of the synthesis will also be explored.

 

Research Area: Materials Sciences
Mentor:  Georgiy Akopov

Catalyst Development for Upgrading Renewable Feedstock

Lignin, as a renewable feedstock, is the only bio-derived source of aromatics in large abundance. The conversion of lignin has been achieved via catalytic reduction with transition metals (Pd, Pt, and Ru) as the catalyst. However, the implementation of the lignin utilization demands the use of less precious transition metals or full replacement with first-row transition metals.

In this project, we will develop metal-based nanocatalyst for lignin conversion. A holistic design will be considered to preserve aromaticity and achieve high selectivity in cleaving ether linkages, including support, metal species, and dopants. Full characterization of the metal catalysts will be conducted such as powder XRD, and scanning transmission electron microscopy. The catalytic reactions will be carried out at elevated temperature and pressure (up to 240 °C and 50 bar).

Research Area: Engineering Chemical
Mentor:  Long Qi

Benchmarking quantum chemistry methods on advanced computers

This project is part of the GAMESS exascale computing project (ECP). GAMESS is an electronic structure theory suite of programs that has about 150,000 users. The project will involve  benchmarking and profiling several core features of GAMESS on the most advanced computers in the DOE system.

Research Area:  Computational Sciences
Mentor:  Mark Gordon

Developing Functionalized Graphene for Biomass Conversion

Developing Functionalized Graphene for Biomass Conversion

 

The goal of this research is to develop low cost catalysts based on graphene-derived nanomaterials, and use them to improve the efficiency of several key steps in biomass refinery. To make the cost of biomass derived fuels comparable, or lower than that of petroleum fuels, it is necessary to develop new catalysts and processes that can substantially improve the efficiency of biomass refinery. Two attractive biomass refinery processes, pyrolysis and hydrolysis of lignocellulose, usually give molecules containing high oxygen content, and thus low energy density to be used directly as fuel. Therefore, upgrading of the lignocellulose derived oxygenates is necessary for them to be fit in appropriated fuel classes (i.e., gasoline, diesel, or jet fuels). The general approaches for upgrading the oxygenates are to decrease their oxygen contents, and to build carbon-carbon bonds, targeting different fuel classes. Catalysts play a vital role in converting and upgrading biomass to fuels, and thus need to be studied extensively. Catalysts based on graphene-derived nanomaterials could greatly improve the efficiency of biomass conversion and substantially decrease the cost of biomass conversion.

 

Research Area:  Renewable Energy Sciences and Technologies
Mentor:  Wenyu Huang

Plastic Upcycling Through Chemical Catalysis

We are developing catalysts for conversion of polymers, the principle component in plastics, from waste materials into new polymers, monomers for repolymerization (recycling), or new valuable chemicals. The vision is that such chemical transformations will provide incentives for collection and processing of plastic waste, which currently are landfilled or discarded on hundred megaton scale. Our approach involves synthesis of supported catalysts and investigation of reactions that break the carbon-carbon bonds polymer chain backbones.

Research Area: Inorganic Chemistry
Mentor:  Aaron Sadow

4DMAPS: Portable sensors for monitoring the rhizosphere

Project will address the challenge of monitoring the physiology and inteactions of plants with other organisms in soil and their responses to the chemical and microbial composition of the rhizosphere.  We will develop a network of aptamer functionalized sensors to monitor the chemicals excreted by plant roots and their interactions with surrounding soil.  The students will design, fabricate and characterize sensors that will be used in the soil monitoring. Nanoporous alumina membranes have become a ubiquitous biosensing platform for a variety of applications and aptamers are being increasingly utilized as recognition elements in protein sensing devices. Combining the advantages of the two, we will utilize the aptamer functionalized alumina membranes for label-free sensitive detection of small molecules using a four-electrode electrochemical cell.  An arduino based reader will be developed to monitor the impedance of the alumina membrane in the four electrode cell configuration.


Research area: Engineering Mechanical
Mentor:  Pranav Shortriya

3D Printing Nanostructures

Over the last couple of decades, scientists have been able to develop a tremendous control over the synthesis and properties of materials at the nanoscale. New, emergent behaviors have been discovered upon investigation of nanostructures. A significant challenge nowadays is how to preserve and extend these nanoparticle behaviors to larger scales, specifically to the macroscale, the world we humans are the most familiar with. To reach this goal we need to create a bridge between the nano and the macro scales, this bridge is known as the mesoscale. We are currently learning and developing tools to orderly assemble nanostructures at the mesoscale, i.e. ordering nanometer sized particles along micron-sized domains. The missing link is putting together micron-sized arrays into millimeter or centimeter sized shapes, and we believe this can be accomplished by 3D printing technologies. In this project, the students will develop inks made up of nanostructured materials so that they can be printed into three dimensional objects that can be as large as a human hand and demonstrate the capacity to organize matter at the nano-, meso- and macro-scales.

 

Research area: Nanoscience

Mentor:  Igor Slowing

Hybrid nanostructures for catalysis

Students will participate in a project aimed to prepare smart multifunctional nanodevices for catalyzing sequences of chemical reactions to convert biomass related products into biorenewable fuels and chemical commodities. The nanostructured materials will be composed of organic and inorganic species that will work cooperatively to effectively promote chemical conversions behaving like nanosized assembly lines. The students will be trained in the synthesis and characterization of hybrid mesoporous materials. They will use a series of analytical methods including powder x-ray diffraction, gas physi- and chemisorption and spectroscopy. Prior experience with any of the mentioned techniques is desirable, but not required, as training will be provided as needed.

Research area: Nanoscience
Mentor:  Igor Slowing

Assembly of Nanoparticles at Solid Surfaces

This project will investigate how to assemble nanostructures at solid interfaces. The nanostructures consist of ordered arrays of nanoparticles capped with hydrocarbon ligands. Following our previously developed methods, we will compute the potential of mean force and free energy of the assembled structures and investigate the ligand textures, with the emergence of ligand vortices, as predicted by the Orbifold Topological Model (OTM), which will be generalized to include interfaces also. The results will be incorporated in our HOODLT software. Although knowledge of Python is not a requisite, willingness to learn it is.  

Research Area: Nanoscience
Mentor:  Alex Travesset

Topological Changes of Electronic Structure during Symmetry-Breaking Structural Transformations in Quantum Systems

While scientifically intriguing, changes of the electronic structure during a lattice transformation offer a means to control aspects of quantum materials for practical applications. In this summer project the student will explore electron-lattice coupling in a model system and how it alters properties. An educational scaffolding and guidance will be provided by the experts in classical and quantum lattice Monte Carlo methods. 

The determinant Quantum Monte Carlo (DQMC) method has been widely applied to investigate magnetic, pairing, and charge correlations of interacting electron Hamiltonians, like the Hubbard model.  Prior investigations have focussed on the square lattice geometry, because of its relevance to physics of the cuprate superconductors, and, more recently, to honeycomb lattices which host Dirac fermions. In this project we propose the DQMC investigation of the Hubbard model on a lattice that interpolates between these geometries.  In other words, we will study the electronic structure during a lattice transformation. 

The student will begin by performing simulations of the classical Ising model on such an interpolating lattice to gain familiarity with Monte Carlo methods.  The student will also learn how to compute tight-binding energy bands for an understanding of the Hubbard model in the noninteracting limit.  The student will adapt an existing DQMC code to the interpolating geometry and run the simulations.  The tight-binding computation will serve as a useful check of the modified code. 

The outcome will be a better understanding of the electron-lattice coupling in a selected class of quantum materials, especially under non-hydrostatic stress during a lattice transformation involving strongly correlated electrons. 

Research area:  Condensed Matter Physics
Mentor:  Nikolai Zarkevich

CMakePP: Facilitating Software Interoperability from the Build System Up

There is significant momentum in computational chemistry to develop a software ecosystem populated with independent, reusable libraries. In theory, these libraries can be easily adopted by any of the various computational chemistry packages, thereby avoiding the metaphorical "reinventing of the wheel." In practice this is a tall order requiring library developers to design for all contact points between their library and the existing software package. Usually the developers of the libraries have given extensive consideration to the application programming interface (API), but particularly for compiled libraries, typically little consideration has been afforded to ensuring that the library also integrates with the existing software package's build system. While this may seem like a trivial consideration, the reality is that the build systems for most existing software packages are extremely complex, tightly coupled, and fragile. Consequentially leveraging these reusable libraries often requires significant effort on the software package side. Making matters worse this additional effort is often hidden from the community because build systems are often an afterthought. The proposed research seeks to develop CMakePP, an extension to the popular CMake build system, which will make adding additional libraries as effortless as possible.  The power of CMakePP will be demonstrated by case studies focusing on integrating some of the more popular reusable libraries with the software package NWChemEx

Research Area: Theoretical Chemistry
Mentor:  Ryan Richard

Investigation of Caloric Refrigeration Concepts

Investigation of Caloric Refrigeration Concepts

 

Caloric materials change temperature in response to externally applied fields (magnetic, stress, electric) and are very promising for replacing conventional vapor-compression systems in cooling applications. Caloric refrigeration has the potential to improve efficiencies while also eliminating the risk of leakage inherent to gaseous refrigerants. Our team at Ames Laboratory has been instrumental in driving the advance of caloric technologies for cooling. The research project will focus on demonstrating early-stage cooling concepts using magnetocaloric and elastocaloric materials.

 

Research Area: Engineering Mechanical
Mentor:  Julie Slaughter

Characterization of Energy Materials by Solid-State NMR Spectroscopy

The properties, activity, and performance of many energy relevant materials are governed by the structure of their surface, subsurface and interfacial regions. For example, the efficiency of solid-state lighting and photo-voltaic (PV) devices based upon semiconductor nanoparticles (NPs) is controlled by the surface termination and the distribution of elements within the NPs . The lack of techniques for atomic-level structural characterization often makes it difficult to test even the basic hypotheses relating materials’ structure to performance and hindering their rational design. In this project, students will develop and apply solid-state NMR spectroscopy to determine the atomic level structure of complex and disordered energy materials such as nanoparticles. This will be accomplished by using the state-of-the-art 263 GHz/400 MHz DNP NMR system hosted in the Ames lab. With DNP and other NMR techniques we can obtain order of magnitude improvements in sensitivity which allow us to characterize dilute sites on the surfaces of nanomaterials.

Research area: Physical Chemistry
Mentor:  Aaron Rossini

Self assembly and crystallization of nano-particles

We modify the surfaces of nano-particles by ligand exchange to promote specific interactions that can invoke self assembly and crystallization of nano-particles into two- and three-dimensional crystals.  The long term goal is to produce so called meta-materials.  We use various X-ray diffraction and spectroscopy techniques to determine the structures of the assemblies.  The student will be involved in all facets of the project including analysis.  Students with background in physics and chemistry with aspirations in materials science will benefit from our lab work.  Basic knowledge of Python or any other language will be helpful.

Research area:  Materials Sciences
Mentor:  David Vaknin

Tuning Magnetic Ordering in Magnetic Materials Containing Rare Earths

The rare earths materials play an increasingly important role in modern technology. Among them, magnetic intermetallic alloys and compounds containing lanthanides are known for their both current (permanent magnets, magnetic actuators) and future (near room temperature magnetic cooling, quantum information) technological applications. The proposed experimental research focuses on magnetic rare earth alloys, in particular on the tuning and control of their magnetic ordering. In our fundamental research we are exploring non-trivial approaches, such as, for example, enhancement of magnetic ordering temperature using chemical substitution of highly magnetic atoms (Gd, Tb, Dy) by non-magnetic atoms (e.g. Sc, Ti).  We are looking for candidates interested in performing experimental synthesis (via melting and heat treatment) and basic characterization (X-ray powder diffraction and magnetic measurements) of ternary and quaternary intermetallic compounds containing one or more rare earth element. The anticipated outcome is a publication in a peer-reviewed science journal.

Research area:  Materials Sciences
Mentor:  Yaroslav Mudryk

Effect of controlled order superconductors using high precision magnetic susceptometer

When a LC circuit is combined with a special semiconductor diode, named a ''tunneling diode'', which has a negative resistance region due to the effect of quantum mechanical tunneling, one can make a high resolution resonator (fundamental frequency of about 14 MHz) with a noise level of 0.05 Hz - one part per billions resolution. This so-called tunnel diode resonator (TDR) technique has been used to probe magnetic property of various magnets and superconductors. In our laboratory, we developed high stability resonator and use it to measure high precision magnetic susceptibility. The student that participates in SULI program will build a hands-on TDR resonator and study the unconventional superconductors which have multiple superconducting gaps under extreme conditions (low-temperature, high-magnetic field, and high-pressure). During this project, the student will learn how condensed matter experimentalists work in the lab from developing tools to acquiring scientific results to writing a research article. Indeed, some of previous SULI students participated in several articles as a coauthor. For more information, please visit our group website.

Research area:  Condensed Matter Physics
Mentor:  Kyuil  Cho

Data Science for Catalysis

Data science has drastically changed how data are collected and analyzed. We would like to introduce new methodologies in data science into catalysis science, which is the key in petroleum refinery and pharmaceutical industries.

In this project, new methods including simulation and modeling, and machine learning will be developed and implemented to increase the instrument efficiency and understand more of the experimental data.

Research area: Physical Chemistry
Mentor:  Long Qi

Catalytic Transformations of Biorenewables

The project is aimed to transform molecules derived from biorenewable sources into commodity chemicals. The student will learn to synthesize and characterize advanced catalysts to perform these transformations under mild conditions in an energy efficient manner. In addition to learn materials characterization techniques, the student will learn methods to monitor reaction progress and to identify target products. Methods may include X-ray diffraction, microscopy, surface physi- and chimisorption, UV/Vis, Infrared, fluorescence and/or NMR spectroscopy, and GC/MS.


Research area: Organic Chemistry
Mentor: Igor Slowing

Security Frameworks for Quantum Computing

As quantum information science (QIS) develops quantum computing architectures and storage, security approaches will be required to create trusted platforms and execution environments.  QIS can be applied to near term utilization for security applications as well as evaluating future quantum architectures that would not be susceptible to classical computing vulnerabilities.  This project aims to collect the current state of simulation/emulation environments including cloud services, cyber-security for quantum computing, and cyber-security utilizing quantum algorithms. This project would then create a framework for further quantum applications, document and create a development environment (e.g. python, Q#, etc.) and demonstrate a quantum algorithm for a cyber-security application such as random number or quantum key generation.


Research area: Engineering Materials
Mentor:  Durga Paudyal

Development of room temperature ferromagnetic nanoparticles for biomedical applications

In collaboration with Virginia Commonwealth University, Ames Laboratory, US Department of Energy, in conducting research on development of new forms of magnetic nanoparticles that show ferromagnetic transition (with high magnetic moment) at or close to room temperature. These nanoparticles have many biomedical applications including MRI contrast agents. These particles can reduce the static magnetic field needed in MRI thus reducing the size and cost of the MRI equipment significantly.  This project will involve preparation of these magnetic nanoparticles and characterization. A patent based on the scalable synthesis of fine particles of one of rare-earth based metal based compound has been granted to the PI and his collaborators. Students working on this topic will have opportunity to get acquainted with the art and science of synthesis of inorganic/hybrid materials and perform cutting edge characterization experiments.  If results mandate, the student will be able to publish their work or submit new patents based on several possible new applications of this material.


Research area: Materials Sciences
Mentor: Shalabh Gupta

Application of 3D Printing Additive Manufacturing Techniques to Lithium-ion Batteries

The project proposes to implement fused filament 3D printing for prototyping high capacity lithium-ion battery (~50-70% of commercial). An experimental protocol will be developed considering combination of different electrolyte, binder, electrochemically active and magnetic-filler materials to produce pliable electrode filaments. Increasing the loading fraction of active electrode material in the filament will be targeted, thus improving the electrochemical capacity. The project proposes to implement magnetic field while printing of magnetically active electrode filaments to align the pores in the inactive material, thus reducing the tortuosity of the printed sample. Electrochemical testing of the printed electrodes will be performed against lithium metal as reference, and also for a full cell to characterize the performance of the cell. Mathematical analysis will be performed to model a 1-D lithium battery and incorporate the impact of pore alignment of the electrochemical transport properties.

The student will be involved in developing several combinations of active material, binder and magnetic filler composites to achieve filaments with highest loading fraction of active material. The student will aid in 3-D printing of the dry electrode and perform electrochemical characterization on the assembled cell. The cell will be assembled, and electrolyte will be prepared by mentor. The student will learn and aid in development of mathematical model for battery simulations.

Research area: Materials Sciences
Mentor:  Ikenna Nlebedim

High Performance Permanent Magnets for Energy Applications

Permanent magnets are increasingly ubiquitous in many applications but are reliant upon expensive rare earth elements which must be obtained from foreign sources. The high cost of expensive rare earth elements is already a threat to technological advancement. Disruption in the supply of these rare earth elements will hinder progress in high-tech and clean energy technologies including wind energy, magnetic resonance imaging, data storage, electric vehicles and many more. As a result, there are global technological and energy security needs to make permanent magnets with reduced or without rare earth elements.

This research will enable students to gain hands-on experience on making powerful permanent magnets. Students will be exposed to our state of the art research equipment for production and testing of magnetic properties. The proposed project will focus mainly on making magnets with reduced or no critical rare earth elements. The student will use our new Controlled Atmosphere Materials Processing System for the research.

As part of the Critical Materials Institute, students will have the opportunity to observe a multi-institutional research project designed to strategically support the competitiveness of the United States in clean energy technologies.

Research area: Materials Sciences
Mentor:  Ikenna Nlebedim

Assembly of nanoparticles by tuning external conditions

This proposal aims at developing the theoretical physics and chemistry of a form of matter that has been emerging during the past twenty years, has already presented with new and exciting fundamental problems and that is now at the point where it may lead to major technological breakthroughs: materials whose elementary components are nanoparticles (nanocrystals, colloids, etc. with dimension between a few and one hundred nanometers) instead of atoms or molecules. The workshop will bring together physicists, chemists and material scientists, both theorists and experimentalists, in an effort to advance the fundamental science of this very young eld. The problems and questions that will be addressed are: Towards programmable matter: Can we control the dynamical scales involved in assembly?  What properties or structures can be realized that are not possible in traditional materials of atoms or molecules?

For that purpose, we will use state of the art computational tools to predict the assembly of different nanocrystals in superstructures.

 

Research area:  Materials Sciences
Mentor:  Alex Travesset

Rare-earth permanent magnets

Rare-earth permanent magnets (REPMs) have excellent magnetic properties and have been widely used in energy conversion and storage, telecommunication, consumer electronics, biomedical devices, and magnetic sensors. However, REPMs are brittle and cannot be used for applications subjected to high stress, vibration or mechanical shock. The brittleness also leads to the magnet production loss up to 20-30% in volume and imposes limitations on part size and shape. This project is to produce REPMs (mainly Sm-Co and Nd-Fe-B sintered magnets) mechanically and magnetically stronger than the commercial products while reducing magnet waste rate to less than 10%. The novel magnets will be more cost-effective, efficient and robust for energy-related applications while reducing the pressure on critical material supply chain.

Research area:  Materials Sciences
Mentor:  Baozhi Cui

Quantitative visualization of atomic columns in materials

Modern aberration-corrected transmission electron microscopy (TEM) and multifunctional detectors provide an unprecedented opportunity to study atom arrangement and chemistry in materials with sub angstrom resolution. With growing data size and complexity, a computational-aided analysis is crucial to extract property-related structural information. This research project will focus on developing atomic-scale image-based quantitative analysis methods for various material systems, including topological magnetic materials and ferroelectric oxides. The student will be involved in developing codes for analyzing and interpreting of results. The knowledge of Python or similar programing language is required.    

Research area: Materials Sciences
Mentor:  Lin Zhou

Tracking dynamics of magnetic topological particles

Magnetic skyrmions are nanoscale vortex-like swirling spin objects that have attracted considerable interest as information carriers for future spintronic devices. Lorentz transmission electron microscopy (LTEM) allows us to observe skyrmions directly in real-space. As atoms in real-crystal, the skyrmion arrangement plays an important role in their formation. This research project will study the kinetics of skyrmion using in-situ LTEM. The student will be involved in developing computational-aided methods for LTEM image analysis. The knowledge of Python or similar programing language is required.

Research area:  Condensed Matter Physics
Mentor:  Lin Zhou

Nano-plasmonic studies of graphene-based van der Waals systems

Surface plasmon polaritons are collective oscillations of charges on the surface of metals or semiconductors. These surface modes are in vogue for their ability to confine and control electromagnetic waves at length scales much shorter than the diffraction limit.  The search for agile plasmonic media is a vibrant research field with promising technological applications. Graphene offers a number of desirable plasmonic characteristics including high confinement, long lifetime, broad spectral range and electrical tunability. These unique properties make graphene a good candidate for plasmonic applications in the technologically-important infrared regime that is not accessible by conventional plasmonics based on noble metals. Despite all the above merits, the plasmonic properties and functionalities of single-layer graphene alone are still limited. One convenient way to engineer graphene plasmons is by constructing van der Waals (vdW) coupled systems based on graphene and/or other layered materials. Indeed, the two-dimensional (2D) nature of graphene makes it extremely sensitive to interlayer coupling that could dramatically modify the properties of Dirac fermions and their plasmonic excitations. In this project, the undergraduate student will work with graduate students to explore novel plasmonic properties and functionalities through systematic nano-infrared studies of various types of graphene-based vdW systems. The objectives of this research are (1) to design and fabricate graphene-based vdW systems by accurately controlling the stacking order, (2) to excite, probe, and characterize plasmons in these vdW structures with the advanced near-field nanoscope, (3) to extract essential parameters of the observed plasmons through rigorous modeling of the experimental data, (4) to achieve active control and manipulations of these plasmons by electrical gating and optical pumping.

Research area: Condensed Matter Physics
Fei Zhe

Quantum information science- modeling the control of qubits

Quantum information science (QIS) is one of the fastest evolving fields of science and technology, that holds enormous potential for quantum computing, communication and information storage. QIS has promise for solving computational problems that can not be presently accomplished. While the classical bit exists in 2 states 0 and 1, the basic element in QIS is the qubit – represented by a local spin vector. Since the spin vector can point in any direction, potentially far greater information can be stored in a qubit than a classical bit.

A very attractive solid-state qubit that we are studying consists of a rare earth (RE) ion in an insulating host crystal. The RE ion has a spin moment that can be addressed and controlled.

In this project we will model the behavior of these qubits in nanocavities that enhance the intensity of light in the cavity, and enhance the interaction of light with the qubit. We will simulate how the state if the qubit can be changed with external photons.

Research area: Condensed Matter Physics
Mentor:  Rana Biswas

Growth and characterization of novel intermetallic compounds

The SULI student will learn the fundamentals of single crystal growth of new materials, primarily using high temperature solution growth.  Depending on the interests of the student and current efforts in the group systems with superconducting, magnetic, structural, and/or electronic transitions will be studied.  The SULI student will also become familiar with measurements of thermodynamic (magnetization) and transport (resistivity) properties.

Research area: Condensed Matter Physics
Mentor:  Paul Canfield

Computational Studies of Heterogeneous Catalysis

Ames Laboratory scientists have synthesized and characterized various mesoporous silica nanoparticles (MSN) which have proven to be excellent heterogeneous catalysts. We will perform quantum chemistry calculations to study the mechanisms for reactions such as the nitroaldol reaction in MSN.

Research area: Theoretical Chemistry
Mentor:  Mark Gordon

Assembly of Magnetic Two-Dimensional Materials

Two dimensional (2D) magnetic materials are promising materials for next-generation of spintronic devices due to appealing properties, such as high flexibility, optical transparency, and high electron mobility, of layered van der Waals materials when exfoliated to the monolayer limit. For spintronic applications, the major challenges are to enhance Curie temperature, perpendicular magnetic anisotropy (PMA), and sensitivity of PMA to the electric field. These properties can be tuned by doping, interfacing with metal layers, elastic strain, or by controlling stacking and relative in-plane orientation of the atomic planes. These factors comprise a complex parameter space in optimizing these properties. Our strategy is to combine material synthesis, high-resolution transmission electron microscope experiments, and the predictive power of ab initio calculations to control the structure and tailor the functional properties of the 2D magnetic materials. Systems of interest include VI3, CrI3, Fe3GeTe2, and Cr2Ge2Te6. The work will provide insight into the structure-properties relationship in these materials and potentially lay a foundation for a broader scope of research. Students will collaborate with local experimentalists.

Research area: Materials Sciences
Mentor:  Liqin Ke

Electronic structure of rare earth materials

The rare-earth metals are becoming increasingly applicable in our everyday life. The enormous importance of rare-earths in the technology, environment, and economy is attracting scientists all over the world to investigate them starting from the extraction to the physical and chemical properties measurements.  Although a lot of works have been done on the experimentation of rare-earths, the true understanding from theory and modeling on these materials is lagging behind. Here, we propose to perform systematic theoretical research from the density functional theory applicable to rare-earths and also study suitable models in order to compare their finite temperature properties obtained from precise experiments.

Research area: Engineering Materials
Mentor:  Durga Paudyal

 Spring 2020

Synthetic Microbiomes for Exploring Plant-Microbe Interactions

We are interested in developing a deeper understanding of how plants interact with both beneficial and detrimental microbes in the rhizosphere.  The rhizosphere represents a critical interface between plant roots and the surrounding soil, harboring a microbial community mediating carbon and nitrogen transformations essential for sequestering carbon and for agricultural productivity.   This microbiome produces a suite of chemicals that facilitate not only interactions with other microbes but also with plants themselves. This project will build a test-bed for a new instrument for detecting specific molecules produced by microbes or the plant in the rhizosphere.  These nucleic acid-based sensors integrated into a nanoporous, alumina membrane platform will send signals to a computer to render a 3D image of the distribution of targeted chemicals around the root over time (4D). Our contribution is to develop a synthetic microbial community for assessing the efficacy of our imaging system while providing insight into the dynamics and fate of the targeted chemicals in the rhizosphere. We will develop synthetic biology tools for controlling production of targeted metabolites by one microbe and separate tools for detecting targeted metabolites by another.  Through the construction of a “plug-and-play” synthetic community modeled on the natural maize rhizosphere microbiome, we will increase community complexity, including the introduction of natural producers and consumers of the targeted metabolites.

Research area: Engineering Biological (nonmedical)
Mentor:  Larry Halverson

Ordered Intermetallic Compounds for Heterogeneous Catalysis

Precious metals and metal alloys are important heterogeneous catalysts for renewable energies and materials. However, both of them have their limitations. Precious metals have low natural abundance and are expensive. Metal alloys have unstable surfaces due to surface segregation under reaction conditions, which renders the identification of active sites and the understanding of reaction mechanisms difficult. My research group will address these limitations by developing new intermetallic NP catalysts. Intermetallic compounds, which consist of two or more metallic elements, adopt specific crystal structures as well as electronic structures different from the constituent elements. The modified electronic structures of intermetallic compounds make them unique catalytic materials. It has been proposed that such compounds should be treated as new “elements” considering their potential in catalysis. The inherent properties of intermetallic compounds, stable and exhibit a large variety of structures, will help us to discover catalysts with stable surfaces, consisting of more abundant metals, to replace unstable alloy and precious metal catalysts.

Research area:  Materials Sciences
Mentor:  Wenyu Huang

Control heterogeneous catalysis at atomic and electronic-level using metal-organic frameworks

To control heterogeneous catalysis at atomic and electronic-level represents one of the most challenge research areas. Using metal organic frameworks (MOFs) as hosts of metal nanoclusters, we could reach an atomic and electronic-level control of heterogeneous catalysts. MOFs, as novel template materials for the synthesis of metal nanoclusters, have great potentials for catalysis due to their structural diversity, flexibility and tailorability, as well as high porosity. Compared to zeolite, the chemical environment of each cage/cavity of MOFs can be controlled at atomic-level by using different organic linkers. The MOFs with isoreticular structures are particularly interesting because they have exactly the same lattice structure, but different chemical compositions. These different organic linkers or metal ion nodes of MOFs results geometrically identical cages of different chemical environments. Nanoclusters, confined in these cages/cavities, would experience an atomic-level fine-tuned chemical environment, and thus exhibit different activity and selectivity in heterogeneous catalysis. During chemical conversion processes, reactants and reaction intermediates could also sense these chemical environments that could alter their adsorption energy and geometry, which will also affect the reaction activity and selectivity.

Research area:  Nanoscience
Mentor:  Wenyu Huang

Plant/microbe communication with aptamers

The rhizosphere is a thin layer around the roots of a plant where microbes congregate. Some microbes are beneficial and others pathogenic. Plants need microbes in the rhizosphere for their proper nutrition. So, they do things to attract the beneficial microbes. For example, up top 70% of a plant's energy can be excreted through the roots into the surrounding rhizosphere to feed the microbes, some of which convert nitrogen gas into forms like ammonium that can be absorbed by the plant. We are interested in understanding this mutualistic relationship as it occurs in the soil. We are also interested in understanding how plants interact with harmful microbes that sometimes enter the rhizosphere. To gain this understanding, we need to obtain data on the molecular signals by which plants and microbes interact. This project is to build the parts of a new instrument for sensing specific molecules in the rhizosphere. The part we are focusing on first is to build the sensors that will be used to detect the molecules. These sensors will send signals to a central computer which will create a 3D image of the distribution of this chemical around the root over time (4D). To build the sensors we will be selecting and maturing nucleic acid aptamers that specifically recognize the molecules of interest. Similar in their function to antibodies, aptamers have properties that are much more applicable to functioning underground than do antibodies. Once selected and matured, the aptamers will be integrated into a nanoporous anodized aluminum oxide sensing platform to create a sensor that will be placed at the tips of the instrument to be placed in the soil for molecular recognition.

Research area:  Engineering Biological (nonmedical)
Mentor: Marit Nilsen-Hamilton

Design of Physically Motivated Anisotropic Atomic Orbital Basis Sets

The goal of theoretical chemistry is to explain and predict chemical phenomena.  Physically we know that such phenomena are described by the Schrödinger equation (SE); unfortunately, analytic solutions to the SE do not exist for most chemical systems of interest. Nonetheless, it is possible to approximate the SE, to arbitrary accuracy, starting from the familiar linear combination of atomic orbitals (AO) ansatz.  The AOs in this ansatz are numeric approximations to the familiar s, p, d, f, etc. orbitals introduced in general chemistry.  Such AOs are well suited for describing an isolated atom, but poorly describe the anisotropic electronic environments found around atoms in molecular environments.  The goal of this project is to extend the traditional AO basis sets so that the resulting basis sets includes anisotropy. The resulting anisotropic AOs (AAO) are the numeric analogs of the traditional spsp2, sp3, ... hybrid AOs.  Because AAOs better describe the anisotropic electronic environments within molecules, It is anticipated that AAO ansätze for molecular systems will be shorter compared to traditional, similar quality, AO ansätze. Given that the time to approximate the SE scales non-linearly with respect to the number of AOs, this means that AAOs should reduce the time needed to approximate the SE.  Resultantly, AAOs have the potential to extend the domain of chemical systems to which theoretical chemistry is applicable.

Research area:  Theoretical Chemistry
Mentor:  Richard Ryan

Synthesis and characterization of novel pnictide materials

Pnictides exhibit a diverse range of properties ranging from thermoelectric materials to high-temperature superconductors. Our research group work on synthesis, structural and properties characterization of novel complex pnictide materials containing transition and/or rare-earth metals. The project will include solid-state synthesis of novel compounds, determination of their crystal structure, and characterization of the electrical and heat transport properties.

Resarch area: Materials Sciences
Mentor:  Kirill Kovnir

Prediction of new materials and properties using machine learning (ML) approaches

The screening of novel materials with good performance and the modelling of quantitative structure-property relationships, among other issues, are hot topics in the field of materials science. Traditional computational modelling often consume tremendous time and resources and are limited by their theoretical foundations. Thus, it is imperative to develop a new method of accelerating the discovery and design process for novel materials. Recently, materials discovery and design using machine learning have been receiving increasing attention and have achieved great improvements in both time efficiency and prediction accuracy. Here we intend to introduce machine learning for rare earth containing materials, propose possible algorithms to predict new materials. By directly combining computational studies with available experimental data, we hope to provide insight into the parameters that affect the properties of materials, thereby enabling more efficient and target oriented research on materials discovery and design.

Research area: Engineering Materials
Mentor:  Durga Paudyal

Multifunctional Catalysts based on Zeolites

Zeolites are microporous crystalline materials composed of alumino-silicate or phosphate. Because of the high thermal stability and strong acidobascity, zeolites have been widely applied in refinery industry. Because regular pore morphologies of zeolites to control the diffusion and formation of molecules of different sizes, zeolites are often called molecular sieves. Besides, zeolites have also used as a support to accommodate molecular metal complexes or metal nanoparticles. The resulting materials become bifunctional, bearing both acidobascity of the zeolites and redox activity from the metals.

We would like to apply zeolites as support for molecular organometallic complexes with rare earth metals and early transition metals, using a chemical liquid deposition method (CLD). The metal will bond directly with isolated bridging oxygen sites in the zeolite, resulting in a bifunctional catalyst. The catalyst can retain the microporous structure and enable hydro-treatment of both fossil and biomass resources. The hydrogenation activation and subsequent reactions will be studied with in situspectroscopy including diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and operando high temperature/pressure solid-state NMR.

Research Area: Materials Sciences
Mentor: Long Qi

Development of Quantum Sensors for Quantum Materials Research

Quantum materials such as superconductors and magnetic skyrmions show promise for advanced technologies including energy-efficient electronics, and technologies based on quantum information science (QIS). Realization of such advanced technologies depend on how well we understand fundamental physics of the relevant quantum material. This requires novel methods of sensing and characterization with better sensitivity and minimal effect on the studied system. In other words, quantum materials need quantum methods of sensing.

Here at Ames Laboratory, we develop new techniques to study magnetic and electronic properties of quantum materials. One of them is based on the nitrogen-vacancy (NV) atomic defect in diamond. This “NV-center” can be viewed as an electron “trapped” in diamond crystal and we access quantum energy levels of electron spin to detect the presence of very weak magnetic fields.

The SULI student will learn the techniques of quantum sensing and atomic force microscopy (AFM) and develop multi-disciplinary hands-on skills working with optical, electronic, and microwave networks. Essentially, the student will learn how condensed matter physicist works in the lab, starting from the development and improvement of the experiment, acquisition of scientific data, and to writing research reports potentially resulting in peer-reviewed journals.

Research area:  Condensed Matter Physics
Mentor:  Naufer Nusran

Exploration of Complex Metal Pnictides Containing refractory Metalloids, Boron and Carbon

The project will investigate ternary and quaternary intermetallics containing refractory metalloid (B, C) and pnictogen (P, As, Sb, Bi). A novel synthetic approach will be developed by binding metals and metalloids in one compounds and than reacting it with volatile pnictogen. Novel phases will be synthesized with unique crystal structures due to flexibility provided by the presence of two non-metal elements able to form strong covalent bonds. Presence of transition and rare-earth metal will provide local magnetic moments and strong spin-orbit coupling which will result in exciting magnetic and transport properties. Properties tunability will be the main focus to realize quantum materials based on the proposed objects of study. Using computational input, the stability of such quaternary phases for second and third row transition metals, as well as systems contaning boron and carbon will be investigated. The mechanism of the synthesis will also be explored.

Research Area: Materials Sciences
Mentor:  Georgiy Akopov

Imaging and Exploiting Nanoscale Heterogeneities

Our research focuses on using imaging methods to discover and to exploit nanoscale heterogeneity in various systems.  Laser-based detection systems and sophisticated data analysis are employed in the process.  Our work is highly collaborative and involves other DOE-funded researchers.

Research Area:  Analytical Chemistry
Mentor:  Jacob Petrich

Catalyst Development for Upgrading Renewable Feedstock

Lignin, as a renewable feedstock, is the only bio-derived source of aromatics in large abundance. The conversion of lignin has been achieved via catalytic reduction with transition metals (Pd, Pt, and Ru) as the catalyst. However, the implementation of the lignin utilization demands the use of less precious transition metals or full replacement with first-row transition metals.

In this project, we will develop metal-based nanocatalyst for lignin conversion. A holistic design will be considered to preserve aromaticity and achieve high selectivity in cleaving ether linkages, including support, metal species, and dopants. Full characterization of the metal catalysts will be conducted such as powder XRD, and scanning transmission electron microscopy. The catalytic reactions will be carried out at elevated temperature and pressure (up to 240 °C and 50 bar).

Research Area: Engineering Chemical
Mentor:  Long Qi

3D Printing Nanostrutures

Over the last couple of decades, scientists have been able to develop a tremendous control over the synthesis and properties of materials at the nanoscale. New, emergent behaviors have been discovered upon investigation of nanostructures. A significant challenge nowadays is how to preserve and extend these nanoparticle behaviors to larger scales, specifically to the macroscale, the world we humans are the most familiar with. To reach this goal we need to create a bridge between the nano and the macro scales, this bridge is known as the mesoscale. We are currently learning and developing tools to orderly assemble nanostructures at the mesoscale, i.e. ordering nanometer sized particles along micron-sized domains. The missing link is putting together micron-sized arrays into millimeter or centimeter sized shapes, and we believe this can be accomplished by 3D printing technologies. In this project, the students will develop inks made up of nanostructured materials so that they can be printed into three dimensional objects that can be as large as a human hand and demonstrate the capacity to organize matter at the nano-, meso- and macro-scales.

 

Research area: Nanoscience
Mentor:  Igor Slowing

Growth and characterization of novel intermetallic compounds

The SULI student will learn the fundamentals of single crystal growth of new materials, primarily using high temperature solution growth.  Depending on the interests of the student and current efforts in the group systems with superconducting, magnetic, structural, and/or electronic transitions will be studied.  The SULI student will also become familiar with measurements of thermodynamic (magnetization) and transport (resistivity) properties.

 

Research area: Condensed Matter Physics
Mentor:  Paul Canfield

Nano-plasmonic studies of graphene-based van der Waals systems

Surface plasmon polaritons are collective oscillations of charges on the surface of metals or semiconductors. These surface modes are in vogue for their ability to confine and control electromagnetic waves at length scales much shorter than the diffraction limit.  The search for agile plasmonic media is a vibrant research field with promising technological applications. Graphene offers a number of desirable plasmonic characteristics including high confinement, long lifetime, broad spectral range and electrical tunability. These unique properties make graphene a good candidate for plasmonic applications in the technologically-important infrared regime that is not accessible by conventional plasmonics based on noble metals. Despite all the above merits, the plasmonic properties and functionalities of single-layer graphene alone are still limited. One convenient way to engineer graphene plasmons is by constructing van der Waals (vdW) coupled systems based on graphene and/or other layered materials. Indeed, the two-dimensional (2D) nature of graphene makes it extremely sensitive to interlayer coupling that could dramatically modify the properties of Dirac fermions and their plasmonic excitations. In this project, the undergraduate student will work with graduate students to explore novel plasmonic properties and functionalities through systematic nano-infrared studies of various types of graphene-based vdW systems. The objectives of this research are (1) to design and fabricate graphene-based vdW systems by accurately controlling the stacking order, (2) to excite, probe, and characterize plasmons in these vdW structures with the advanced near-field nanoscope, (3) to extract essential parameters of the observed plasmons through rigorous modeling of the experimental data, (4) to achieve active control and manipulations of these plasmons by electrical gating and optical pumping.

Research area: Condensed Matter Physics
Mentor:  Zhe Fei

Quantum information science-- modeling the control of qubits

Quantum information science (QIS) is one of the fastest evolving fields of science and technology, and holds enormous potential for quantum computing, communication and information storage. QIS has promise for solving computational problems that can not be presently accomplished. While the classical bit exists in 2 states 0 and 1, the basic element in QIS is the qubit – represented by a local spin vector. Since the spin vector can point in any direction, potentially far greater information can be stored in a qubit than a classical bit.

A very attractive solid-state qubit that we are studying consists of a rare earth (RE) ion in an insulating host crystal. The RE ion has a spin moment that can be addressed and controlled.

In this project we will model the behavior of these qubits in nanocavities that enhance the intensity of light in the cavity, and enhance the interaction of light with the qubit. We will simulate how the state if the qubit can be changed with external photons.

Research area:  Condensed Matter Physics
Mentor:  Rana Biswas

Electronic structure of rare earth materials

Rare-earth metals are becoming increasingly applicable in our everyday life. The enormous importance of rare-earths in technology, environment, and the economy is attracting scientists all over the world to investigate them, beginning with the extraction to physical and chemical properties measurements.  Although a lot of work has been done on the experimentation of rare-earths, true understanding from theory and modeling on these materials is lagging behind. Here, we propose to perform systematic theoretical research from the density functional theory applicable to rare-earths and also study suitable models in order to compare their finite temperature properties obtained from precise experiments.

 

Research area:  Engineering Materials
Mentor:  Durga Paudyal